2024 ר Nexus Grant Awards

Using advanced computational analysis to predict ovarian cancer outcomes

ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Anschutz PI: (Obstetrics and Gynecology)
ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Boulder PI: Aaron Clauset (Computer Science; BioFrontiers Institute)
​ÌýÌýExisting collaboration ($125K)
ÌýÌýTrack 2: AI, Advanced Computing, Quantum & Human Health (Cancer)

This project will develop advanced bioinformatic tools to synthesize large-scale transcriptomic data from ovarian tumors and to predict tumor remodeling caused by chemotherapy to improve patient outcomes in ovarian cancer.

Using advanced computational analysis to predict ovarian cancer outcomes

Improved assessment of placenta accreta with fast 3D MRI

ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Anschutz PI: (Biomedical Informatics;ÌýRadiology;ÌýApplied Mathematics)
ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Boulder PI: Stephen Becker (Applied Mathematics)
​ÌýÌýExisting collaboration ($125K)
ÌýÌýTrack 2: AI, Advanced Computing, Quantum & Human Health

Magnetic Resonance Imaging (MRI) is limited by its long scan time and the requirement that the subject remain still; this precludes the usage of 3D MRI of the abdomen during pregnancy due to the ever-present motions of the fetus. With the ר Nexus award, we will develop deep-learning based methods to generate high-quality and anatomically accurate images from data collected with a faster MRI scan, which will mitigate the effects of fetal motion.

Improved assessment of placenta accreta with fast 3D MRI

Cell-type, pathway and neurotransmitter-specific regulation of feeding circuitry

ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Anschutz PI: (Pharmacology)
ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Boulder PI: David Root (Psychology and Neuroscience)
​ÌýÌýExisting collaboration ($125K)
ÌýÌýTrack 0: Broad Initiative

This project seeks to identify how a brain region involved in anxiety disorders affects feeding-related behaviors, as well as the specific pathways, type of neurons, and molecules involved. Results may generate new directions against eating disorders, which highly interact with anxiety.

Cell-type, pathway and neurotransmitter-specific regulation of feeding circuitry

Investigating extreme health risks at the nexus of climate change, incarceration and societal re-entry in Å·ÃÀ¿Ú±¬ÊÓƵ

ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Anschutz PI: (Medicine)
ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Boulder PI: David Ciplet (Environmental Studies)
​ÌýÌýNew collaboration ($75K)
ÌýÌýTrack 1: Climate Change and Human Health

Incarceration creates the perfect storm for mental health crises and contributes to deteriorating physical health. Health risks in carceral environments are increasingly compounded by climate hazards including extreme temperatures, a lack of policies to protect incarcerated individuals from these temperatures, and pre-existing poor carceral infrastructure. The objective of this proposal is to identify the infrastructural, institutional, and epidemiological drivers of health risks related to extreme temperatures in Å·ÃÀ¿Ú±¬ÊÓƵ prisons.

Investigating extreme health risks at the nexus of climate change, incarceration and societal re-entry in Å·ÃÀ¿Ú±¬ÊÓƵ

How tubulinopathies disrupt microtubules and how to fix them: an integration of genetics and computational modeling

ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Anschutz PI: (Cell and Developmental Biology)
ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Boulder PI: Meredith Betterton (Physics; Molecular, Cellular and Developmental Biology)
​ÌýÌýExisting collaboration ($125K)
ÌýÌýTrack 0: Broad Initiative

Devastating defects in human nervous system development known as ‘tubulinopathies’ are caused by heterozygous missense mutations in tubulins, a family of proteins that make up the subunits of microtubules. The goal of this proposal is to generate the first-ever integrated dataset and model to measure and predict the effects of tubulin mutants on kinesin motors important for brain development, by testing the novel hypothesis that tubulin mutants create outsized effects through allosterically modulating neighboring tubulin subunits.

How tubulinopathies disrupt microtubules and how to fix them: an integration of genetics and computational modeling

Cell cycling adaptations in drug-tolerant persister cells in non-small cell lung cancer treated with tyrosine kinase inhibitors

ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Anschutz PI: (Medical Oncology)
ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Boulder PI: Sabrina Spencer (Biochemistry; BioFrontiers Institute)
​ÌýÌýNew collaboration ($75K)
ÌýÌýTrack 0: Broad Initiative (Cancer)

The success of targeting these oncogenic drivers with oral tyrosine kinase inhibitors (TKIs) has resulted in significant improvements in objective response rates, progression free survival and overall survival, but unfortunately, acquired resistance to TKIs is inevitable and remains a major clinical challenge. Re-entering the cell cycle is a critical step for cancer cells to escape the effects of TKIs and form acquired resistance. This proposal will leverage novel techniques using patient derived samples to better characterize how lung cancer cells re-enter the cell cycle on treatment and develop acquired resistance.

Cell cycling adaptations in drug-tolerant persister cells in non-small cell lung cancer treated with tyrosine kinase inhibitors

AI-optimized pacing for heart failure patients

ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Anschutz PI: (Cardiology)
ÌýÌýÅ·ÃÀ¿Ú±¬ÊÓƵ Boulder PI:ÌýAshutosh Trivedi (Computer Science)
​ÌýÌýNew collaboration ($65K)
ÌýÌýTrack 2: AI, Advanced Computing, Quantum & Human Health

This study seeks to apply a type of artificial intelligence called reinforcement learning to finding the best device settings for patients with pacemakers to prevent heart failure events.

AI-optimized pacing for heart failure patients